JP6223932B2 - Microorganism detection method, microorganism detection apparatus, and program - Google Patents

Description

  The present invention relates to a microorganism detection method, a microorganism detection apparatus, and a program for detecting a colony of microorganisms such as fungi and fungi in a medium using, for example, a petri dish.

  Patent Documents 1 and 2 disclose a microorganism detection method (colony detection method) in which microorganisms generated in a petri dish medium are detected and colonies are counted. In this microorganism detection method, a petri dish containing a medium in which microorganisms are cultured is photographed with a camera, and the number of microorganism colonies in the medium region in the image is counted based on the image.

  By the way, in this type of inspection, there are cases where the presence or absence of colonies is important and cases where the number of colonies generated is important. In the former case, the colony detection accuracy is important, but in the latter case, the colony counting accuracy is important.

  For example, in Patent Document 1, a petri dish is imaged at different rotation angles with a camera, and colonies overlapping in the thickness direction of the medium are distinguished and counted as much as possible from the number of colonies counted in the medium in a plurality of images with different rotation angles. . That is, even if a plurality of colonies overlap and are counted as one in an image captured at a certain rotation angle, the plurality of colonies are separated and counted separately in an image captured from another different rotation angle. Thus, by comparing the corresponding colonies between a plurality of images with different rotation angles, it is possible to separately calculate a plurality of overlapping colonies and calculate a more correct number of colonies.

  Further, in Patent Document 2, the image area to be inspected is divided into a central area and a peripheral area, the number of colonies in the central area is counted, and the number of colonies in the peripheral area is a predetermined ratio with respect to the number of colonies in the central area. Consider the total number of colonies. For this reason, in the peripheral region, the medium becomes thick at the meniscus in the vicinity of the inside of the side wall portion of the petri dish, and there is a difference in density from other parts, or along the side wall portion due to the influence of light refracted on the side wall portion of the petri dish Even if dark and light rings are formed on the medium, the number of colonies can be counted relatively accurately.

JP 2008-295424 A JP 2006-345750 A

  However, in the microorganism detection method described in Cited Document 1, a plurality of colonies that overlap in the thickness direction of the medium and a colony that overlaps the bubbles can be counted using a plurality of images with different rotation angles. If the distance between the two is zero or considerably short and any image with a different rotation angle cannot be separated, the colonies cannot be counted accurately.

  Moreover, in the microorganism counting method described in Patent Document 2, the counting accuracy of the number of colonies depends on the number of colonies in the central region. For this reason, when a colony connected to or overlapping with bubbles in the central region cannot be detected, the colony counting accuracy of the central region is relatively low, and in the peripheral region calculated as a predetermined ratio with respect to the counted value Since the accuracy of the estimated value of the number of colonies deteriorates, the colony counting accuracy decreases. Therefore, there is a demand for a microorganism detection method that can detect microorganisms with relatively high accuracy even if foreign substances such as bubbles and microorganisms are connected or overlapped. Note that the above-mentioned problems are not limited to the colony counting, and the same applies to microorganism detection methods for examining microorganisms.

An object of the present invention is an image obtained by photographing the inspection object can be detected foreign matter, microorganism detection method capable of obtaining a detection accuracy of the relatively high microorganism is to provide a microorganism detection apparatus, and a program.

Hereinafter, means for solving the above-described problems and the effects thereof will be described.
A microorganism detection method for solving the above-described problem is a microorganism detection method for detecting microorganisms cultured in a medium, and in the inspection object image region in an image obtained by photographing the inspection object including the medium, An extraction step for extracting a region where a microbial colony may exist as a colony candidate based on the difference in color, and determining whether the colony candidate is circular, whether the colony candidate is a foreign object, An annular determination step for determining whether a plurality of colonies are consecutive colony candidates,
And a foreign substance removing step of extracting the colonies subjected to foreign matter removing process of removing colony candidates it is determined that the foreign matter in the annular determination step.

According to this method, in the extraction step, colony candidates are extracted based on the density or color difference from the culture medium in the inspection target image region. Further, it is determined whether or not the colony candidate includes a foreign substance in the circular determination step. The foreign matter removing step, foreign substance removal process is performed on colonies candidate colonies are extracted by the foreign matter is divided.

I I, it is possible to reduce the number of colonies candidates to be subjected to the foreign matter removal processing, it is possible to suppress the total processing time required for until you detect colonies relatively short.

The microorganism detection method preferably further includes a counting step of counting the number of colonies including the number of colonies extracted by the foreign substance removal process.
According to this method, the number of colonies including the number of colonies extracted by the foreign substance removal process is counted in the counting step. Therefore, the colony counting accuracy is improved as compared with the case where the foreign matter removing process is not performed.

  The microorganism detection method further includes a determination step of determining whether or not the colony candidate includes a foreign substance, and the foreign substance removal step includes removing the foreign substance with respect to the colony candidate determined to include the foreign substance in the determination step. It is preferable to perform the treatment.

In the microorganism detection method, prior to the circular determination step , a convexity determination step for determining whether the convexity of the colony candidate is a set value or less, and both ends of the colony candidate for which the convexity is a set value or less it is preferable that the obtaining further Bei a connecting process step of connecting the auxiliary lines.

According to this method, the convexity degree is determined for the colony candidate in the convexity degree determination step. In the connection process step, a connection process for connecting both ends of the colony candidate whose convexity is equal to or less than a set value on the image is performed. The annular determination step is executed after the connection processing step. Therefore, even if the foreign matter that appears in a normal ring shape, such as a bubble, has an arc shape with a part cut, it is determined as a foreign matter in the ring determination step because it is formed into a ring shape by the connection process. Therefore, a colony candidate including a foreign substance such as an arc-shaped bubble can be a target for the foreign substance removal process, and the colony detection accuracy is improved accordingly.

In the microorganism detection method, a separation determination step for determining whether or not the candidate for colony after the foreign matter removal process in the foreign matter removal step is a separation target that may include a plurality of colonies; It is preferable to further include a separation step of performing a separation process on the colony candidate determined as the separation target.

  According to this method, the colony candidate determined to be separated after the foreign substance removal process is performed is subjected to the separation process, and those that can be separated are separated into a plurality of colonies. Therefore, the colony detection accuracy is improved. For example, when counting detected colonies, the counting accuracy is also improved.

In the microorganism detection method, the foreign matter removal process is preferably a shape extraction process for extracting a shape of a region having a size exceeding a threshold value in a colony candidate.
According to this method, in the foreign substance removal process, the shape extraction process is performed to extract the shape of the region having a size exceeding the threshold value in the colony candidate. As a result, foreign matters having a size equal to or smaller than the threshold can be removed, and colonies having a size exceeding the threshold can be left.

In the microbe detection method, the shape extraction process is performed by extracting a circle collection area in which a circle diameter is designated as the threshold, and a circle having a designated diameter can be inscribed in the colony candidate area , It is preferable to include a process of removing at least a part of a region occupied by a foreign substance other than the colony with respect to the colony candidate . According to this method, when a shape extraction process is performed on a colony candidate, a circle collection region in which a circle having a specified diameter can be inscribed in the colony candidate region is extracted. As a result, some areas of colony candidates that are narrower than the specified diameter (for example, arc-shaped areas of bubbles and areas of linear foreign objects) are removed, and colonies that are areas where a circle with the specified diameter can be inscribed Are extracted. Therefore, it is possible to remove a bubble or a linear foreign object from a colony candidate that is connected or overlapped with a foreign substance such as a bubble and extract a colony.

  In the microorganism detection method, the inspection target image region is divided into a central region and a peripheral region, and the extraction step further includes a polar coordinate conversion step for performing a polar coordinate conversion on the peripheral region, and in the image of the peripheral region after the polar coordinate conversion, It is preferable to extract colony candidates in the peripheral region.

  According to this method, in the extraction step, colony candidates in the peripheral region are extracted from the image of the peripheral region after the polar coordinate conversion. Therefore, the colony candidates existing in the periphery of the container of the inspection object are extracted from the meniscus or refracted light of the medium. Extraction can be performed relatively accurately without being disturbed by the influence of.

In the foreign matter removing step, it is preferable that the foreign matter removing process is performed on the colony candidates in the peripheral region image after the polar coordinate conversion.
According to this method, the foreign substance removal process is performed on the colony candidates in the peripheral area image after the polar coordinate conversion. It is easy to extract colony candidates in the peripheral area, and foreign matter can be removed without taking correspondence from the polar coordinates to the original coordinates.

A microorganism detection apparatus that solves the above-described problem is a microorganism detection apparatus that detects microorganisms cultured in a culture medium, and in a test object image region in an image obtained by photographing a test object including the culture medium, Based on the difference in color, an extraction unit that extracts a region where a microbial colony may exist as a colony candidate, and determines whether the colony candidate is circular, whether the colony candidate is a foreign object, comprising a determining annular determining section for determining a plurality of colonies is continuous colonies candidates, and performs a foreign object removing process for removing foreign matter other than the colony foreign substance removal processing unit which extracts a colony to the colony candidate ing.

According to this configuration, the colony candidate is extracted by the extraction unit based on the density or color difference from the culture medium in the inspection target image region. The circular determination unit determines whether or not the colony candidate is circular, and determines whether the colony candidate is a foreign substance or a colony candidate in which a plurality of colonies are connected. The foreign substance removal processing unit, the foreign matter removal processing is performed on the colony candidate colonies are extracted by the foreign matter is divided. I, to improve the detection accuracy of the colony. Furthermore, the number of colony candidates to be subjected to the foreign substance removal process can be reduced, and the total processing time required until the colony detection is completed can be kept relatively short.

A program for solving the above-described problem is a program for causing a computer to execute a microorganism detection process for detecting microorganisms cultured in a medium, and the inspection object image in an image obtained by photographing the inspection object including the medium on the computer. In the region, an extraction step for extracting a region where a microbial colony may be present based on the difference in color or color from the medium as a colony candidate, and determining whether the colony candidate is circular, whether the colonies candidate is foreign body, an annular judgment step of judging whether the colony candidates continuous multiple colonies, removing foreign matter other than the colonies against determined colonies candidate as foreign in the annular determination step A foreign matter removing step of performing a foreign matter removing process to extract colonies. When this program is executed by a computer, the same effects as the above-described microorganism detection method can be obtained.

According to the present invention, in an image obtained by photographing the inspection object can be detected foreign material, it is possible to obtain the detection accuracy of the relatively high microbial, excellent effect can be obtained.

The schematic side view which shows the test | inspection system in one Embodiment. The schematic diagram which shows the sample of the test object image | photographed with the camera. The block diagram which shows the electrical structure and functional structure of a test | inspection system. (A)-(c) is a schematic diagram explaining the extraction process including the polar coordinate transformation of an outermost periphery area | region. (A)-(i) is a schematic diagram which shows the example of a colony candidate. (A), (b) is a schematic diagram explaining the auxiliary line connection process with respect to a colony candidate. (A)-(e) is a schematic diagram explaining the detail of a shape extraction process. (A)-(e) is a schematic diagram explaining the shape extraction process with respect to a bubble candidate. The flowchart which shows a colony count process routine. The flowchart which shows a bubble filter processing routine.

Hereinafter, an embodiment according to a microorganism detection device will be described with reference to the drawings.
As shown in FIG. 1, a microorganism testing system (hereinafter simply referred to as “testing system 11”) includes a testing unit 12 in which a sample S, which is an example of a test object, is set for testing, a personal computer 13, It has. The sample S is, for example, a petri dish 30 (see FIG. 2) that houses a medium M in which bacteria are cultured.

  The inspection system 11 detects a colony of fungi generated in the culture medium layer of the sample S after culture. In the inspection room 12 a of the inspection unit 12, an inspection table 15 (inspection stage) for placing the sample S and a camera 16 for photographing the sample S on the inspection table 15 are provided. The sample S is set on the examination table 15 in the examination room 12a at a predetermined time when examination is desired, for example, at an intermediate point or end point of the culture period. The inspection system 11 photographs the sample S set on the inspection table 15 with the camera 16, detects a colony of microorganisms present in the medium of the sample S based on the image of the sample S, and counts the number of colonies. In the present embodiment, a colony is an example of a microorganism.

  An image signal of the sample S taken by the camera 16 is input to the personal computer 13. The personal computer 13 uses the image data of the sample S to detect a microorganism colony (hereinafter, simply referred to as “colony CL”) generated in the medium of the sample S by a predetermined algorithm, and a detection And a counting process for counting the number of colonies formed.

  As shown in FIG. 1, the inspection table 15 provided in the inspection chamber 12 a includes a movable stage 22 provided on a support table 21, and a light source 23 that illuminates a sample S set on the stage 22. , A parallel filter 24, a diffusion plate 25, and a motor 26 that moves the stage 22. The stage 22 has at least a portion on which the sample S is placed formed of a translucent material such as glass. A stopper 27 that can position the petri dish 30 of the sample S at a predetermined position is provided on the upper surface (mounting surface) of the stage 22. The stage 22 is supported so as to be rotatable about an axis parallel to the Z-axis direction orthogonal to the mounting surface with respect to the support base 21, and is configured to be rotatable with the power of the motor 26. The stage 22 can be adjusted in position in the X-axis direction and the Y-axis direction orthogonal to each other in a virtual plane parallel to the placement surface.

  When the sample S on the stage 22 is photographed by the camera 16, the sample S can be photographed at a plurality of different rotation angles by rotating the stage 22 about its axis. Specifically, the stage 22 can be rotated about the axis parallel to the optical axis of the camera 16 by the power of the motor 26. In this case, since the optical axis of the camera 16 and the center of the petri dish 30 do not necessarily coincide with each other, the petri dish 30 is shot by the camera 16 from different shooting angles depending on the rotation angle. Therefore, even when two colonies, for example, in the vicinity of the culture medium in the sample S photographed at a certain rotation angle overlap at the photographing angle of the camera at that time, the camera at that time when photographed from another rotational angle. With the shooting angle, there are cases where the overlapping colonies are shot in a separated state.

  In this case, when the number of colonies is counted in an image taken according to the rotation angle, the colony count value differs depending on whether the colonies overlap or not. For this reason, in this example, the petri dish is imaged a plurality of times at different rotation angles to obtain a plurality of images having different imaging angles, and the number of colonies is counted in each image, for example, based on the maximum count value. To decide.

  The inspection system 11 also uses a microorganism detection processing device (hereinafter simply referred to as “detection processing device 40”) that performs colony detection processing and counting processing based on an image acquired by photographing the sample S on the inspection table 15 with the camera 16. "). The detection processing device 40 is built in the main body 31 of the personal computer 13 into which image data from the camera 16 is taken.

  The light emitted from the light source 23 is converted into parallel light by the parallel filter 24, and the parallel light is diffused by the diffusion plate 25. The diffused light is applied to the lower surface of the sample S (the petri dish 30) through the opening of the support base 21 and the stage 22 made of a translucent material, and the irradiated diffused light passes through the petri dish 30 and the medium M. The camera 16 takes a picture. The camera 16 is arranged at a position away from the distance at which the entire sample S on the inspection table 15 can be photographed. An annular light source is arranged between the camera 16 and the inspection table 15 so that the central axis of the light source 23 and the optical axis of the camera 16 coincide with each other, and the sample S is illuminated from the same direction side as the camera 16. The structure which image | photographs the done image may be sufficient. A power supply device 28 for supplying power to the camera 16, the light source 23, and the motor 26 is disposed in the examination room 12a.

  The camera 16 uses a monochrome camera in this example, but may be a color camera. The camera 16 uses a CCD (Charge Coupled Device) image sensor, a CMOS image sensor, or the like as an image sensor. The camera 16 includes a lens unit 17 having an autofocus function and a zoom function. The camera 16 images the sample S (the petri dish 30) on the inspection table 15 at a predetermined magnification. When a color camera is used as the camera 16, either a three-plate type or a single-plate type can be used.

  The sample S is a petri dish 30 (for example, a glass petri dish) that contains a medium M (agar medium or the like). The petri dish 30 is placed on the inspection table 15 with the lid facing the opposite side to the camera 16 in a state where the plate portion is covered with the lid and turned upside down. This is to prevent bacteria and the like from being mixed into the medium M by removing the lid.

  The personal computer 13 includes a main body 31, an input device 32 including a mouse 32m and a keyboard 32k, and a monitor 33 (display unit). The camera 16 is connected to the main body 31. The camera 16 outputs image data generated by A / D converting an analog signal acquired by an internal imaging device (not shown) to the main body 31. The detection processing device 40 built in the main body 31 performs a detection process and a counting process of microbial colonies in the culture medium M based on the image data input from the camera 16. The detection processing device 40 of the present embodiment corresponds to an example of a microorganism detection device.

  Next, with reference to FIG. 2, an image obtained by photographing the sample S to be inspected by the camera 16 will be described. As shown in FIG. 2, for example, the entire area of the medium M in the petri dish 30 in the image obtained by photographing the specimen S to be examined after a predetermined culture period is set as the examination target image area KA. In the culture medium M in the petri dish 30, a plurality of colonies CL are, for example, scattered. Further, in the medium M, there may be a foreign substance N such as a bubble B or dust that may cause erroneous detection and erroneous counting of the colony CL as noise.

  Here, the petri dish 30 contains a medium M in which a predetermined amount of sample liquid such as drinking water or food to be examined is mixed. When making the sample S, for example, a liquid medium kept at 45 to 50 ° C. is poured into the dish part of the petri dish 30. At this time, bubbles B (see FIG. 2) may be mixed in the medium. When the medium M is solidified without the bubbles B disappearing, the bubbles B are present in the medium M at the time of inspection.

  As shown in FIG. 2, the foreign matter N such as the colony CL, the bubbles B, and dust appears darker than the culture medium M, and the density value is lower than that of the culture medium M. That is, the colony CL is a circular dark region having dark gray or black. In addition, the bubble B is formed of a transparent gas such as spherical air, an annular dark region having a white or light gray hole (for example, a white hole) at the center and a dark gray or black outer peripheral portion. It has become. Moreover, foreign matters such as dust are, for example, fibrous and dark gray or black.

  The medium M in the petri dish 30 is cultured in a constant temperature room for a predetermined culture period under a predetermined temperature condition. The sample S is inspected at least once by the inspection system 11 at a necessary time (for example, after the end of the culture period) until the end of the culture period of the microorganism (test target microorganism). By this inspection, the detection of the colonies CL generated in the medium M of the sample S and the number of the colonies are counted. The bubbles B present in the culture medium M at the time of the inspection may cause erroneous detection and erroneous counting of the colony CL. In addition, since the colony CL is generated at an arbitrary location inside and on the surface of the medium M, a plurality of colonies CL may be connected or overlapped in the photographed image.

  Further, as shown in FIG. 2, in the present embodiment, the inspection target image area KA is divided into a circular central area A1 that occupies most of the area excluding the peripheral edge, and a circle near the outermost periphery located on the outer peripheral side. The outermost peripheral area A2 (an example of a peripheral area) extending in a ring shape is divided by a dividing line indicated by a broken-line circle in FIG. In the outermost peripheral region A2, the culture medium M is thicker than the other regions (inner regions) in the region along the side wall 30a by the meniscus, and the peripheral portion is relative to the inner region due to the difference in thickness of the culture medium M. It becomes darker and there is a difference in shading between the inner region and the peripheral portion. For example, the light refracted by the side wall 30a of the petri dish 30 forms an annular bright part or dark part (shadow part) on the peripheral part of the medium M, and the density of the medium M changes. Thus, in the outermost peripheral region A2, the thickness of the culture medium M becomes relatively high due to the meniscus, and the density is relatively high due to the influence of light refracted by the side wall 30a.

  Therefore, the inspection target image region KA is divided into a circular central region A1 that is hardly affected by the meniscus of the medium M and the refracted light at the side wall 30a, and an outer peripheral side region of the meniscus and the side wall of the medium M. In 30a, it is divided into an annular outermost peripheral region A2 including a peripheral portion considered to have a possibility that a change in shading due to refracted light may affect the inspection. The colonies CL are counted by different methods in the central area A1 and the outermost peripheral area A2. Furthermore, as a method for counting the number of colonies in the outermost peripheral area A2, two methods described later are prepared.

Next, the electrical configuration and functional configuration of the inspection system 11 will be described with reference to FIG.
The inspection unit 12 and the personal computer 13 constituting the inspection system 11 are electrically connected. A computer main body (hereinafter referred to as “computer 38”) having a CPU 35 (central processing unit) and a memory 36 (for example, RAM) is built in the main body 31 constituting the personal computer 13. The computer 38 is connected to the monitor 33 via the input device 32 and the display drive circuit 39. The memory 36 stores a program PR for causing the computer 38 to execute colony counting processing including detection and counting of colonies generated in the medium of the sample S in the image using image data taken by the camera 16. . The computer 38 functions as a detection processing device 40 as an example of a microorganism detection device by executing the program PR read from the memory 36. Details of the detection function and the counting function of microorganisms (colony in this example) by the detection processing device 40 will be described later. The memory 36 uses a part of the storage area of the hard disk or RAM.

  As shown in FIG. 3, the computer 38 is connected to the camera 16 and the light source 23. The computer 38 performs shooting control (focus control, zoom control, etc.) of the camera 16 and illumination control by the light source 23. The computer 38 stores various setting data input by operating the input device 32 in the memory 36. Further, the computer 38 displays an image of the sample S taken by the camera 16, a colony detection result, a count result, and the like on the monitor 33.

  On the other hand, the camera 16 provided in the inspection unit 12 is electrically connected to a computer 38 in the main body 31. The image data of the sample S taken by the camera 16 is transferred to the computer 38 through the cable 18 and stored in a predetermined storage area of the memory 36. The light source 23 and the motor 26 are electrically connected to a computer 38 in the main body 31 via a drive unit 29 (drive circuit). The computer 38 outputs a motor control signal (for example, a motor command value) to a motor source drive circuit (not shown) in the drive unit 29, thereby adjusting the supply voltage from the power supply device 28 to a predetermined voltage by the drive unit 29. The motor 26 is driven and controlled by outputting to the motor 26. By rotating the stage 22 with the power of the motor 26 at this time, the sample S on the stage 22 can be rotated by a predetermined angle. Further, the computer 38 outputs a power supply control signal (for example, a current command value) for controlling the brightness of the light source 23 to a light source drive circuit (not shown) in the drive unit 29, thereby instructing a supply voltage from the power supply device 28. The brightness of the light source 23 is controlled by adjusting to the predetermined voltage and outputting it to the light source 23. The sample S on the stage 22 can be rotated by the power of the motor 26.

  In FIG. 3, each functional block schematically shown in the CPU 35 in the detection processing device 40 is realized by the computer 38 executing the program PR. The detection processing device 40 includes a control unit 41, an image generation unit 42, an extraction unit 43, a foreign matter removal processing unit 44, a first determination unit 45, a second determination unit 46, a third determination unit 47, and a counting unit 48. . The detection processing device 40 performs image input, colony candidate extraction, foreign substance removal processing, colony detection, counting processing, result output, and the like as processing for colony detection and counting. In this embodiment, the colony candidate is extracted based on the difference in contrast with the medium M, and if there is a region where the colony CL of the microorganism may exist in the inspection target image region KA, that is, there is a colony. Refers to the estimated area. The foreign substance removal process is a process of removing at least a part of a region occupied by the foreign substance N other than the colony CL with respect to the colony candidate.

  The control unit 41 controls the entire colony detection process and counting process. The inspector operates the input device 32 in a state in which the setting screen is displayed on the monitor 33 by the control unit 41, and the bacterial species information for specifying the type of bacteria to be examined, the outermost peripheral area A2 of the examination target image area Input method selection information for selecting one of a plurality of detection methods prepared for counting colonies. In the memory 36, data of a determination condition used for determining whether or not it is a colony is stored in association with the bacterial species. The control unit 41 reads out discrimination condition data corresponding to the bacterial species specified by the bacterial species information from the memory 36, reads out setting data including discrimination conditions used for discrimination as to whether or not it is a colony, and the memory 36. Write to the work area.

  Further, the control unit 41 controls zooming and automatic focusing of the camera 16 before photographing the sample S. Then, the control unit 41 receives an image signal obtained by photographing the sample S from the camera 16 through the cable 18 and stores it in a predetermined storage area (for example, a video RAM) of the memory 36. Then, the control unit 41 instructs the respective units 42 to 48 that perform the inspection process in a shared manner according to the respective processes. Further, the control unit 41 displays the image of the sample S taken by the camera 16, the colony detection result, the count of the detected colony, the count result, and the like on the monitor 33.

  In the detection processing device 40 of the present embodiment, two types of counting methods are prepared as a method of counting the colonies in the outermost peripheral area A2. The first counting method is a method in which the stage 22 is rotated, the sample S is photographed a plurality of times at different rotation angles, and the number of colonies in the outermost peripheral area A2 is determined using a plurality of images having different rotation angles. Even if a plurality of colonies are photographed by being connected or overlapped at a certain rotation angle (imaging angle), an image in which the plurality of colonies are separated may be obtained at another rotation angle (imaging angle). . When a plurality of colonies are separated and present at coordinates in consideration of the photographing angle in another image corresponding to the coordinates of one colony candidate on the image, the larger number of colonies is adopted.

  On the other hand, in the second counting method, the number of colonies Co in the outermost peripheral area A2 (an example of the peripheral area) is determined according to the type of bacteria (colony type) and the sample liquid with respect to the colony count value Cc in the central area A1. This is a method that considers a predetermined ratio determined in advance. Predetermined ratios obtained from past measurement data are stored in advance in the memory 36 for each type of bacterial species (colony species) and specimen liquid. In the second counting method, the sum of the colony count value Cc in the central area A1 and the colony count Co in the outermost peripheral area A2 obtained by multiplying the colony count value Cc by a predetermined ratio is the colony count value of the sample S. It is said.

  In the image generation unit 42, the control unit 41 that has received the image signal performs a process of cutting an image including the inspection target image area KA from the image data stored in the predetermined storage area of the memory 36. In the present embodiment, in the image photographed by the camera 16, the side wall 30a of the petri dish 30 has a tapered shape that slightly expands toward the outer periphery as it approaches the opening in the height direction, and is photographed from the bottom side by turning upside down. In the image of the petri dish 30, there is an outermost peripheral annular portion in which the peripheral edge of the culture medium M is captured through the side wall 30a. In this embodiment, a circular inspection target image area KA including the outermost peripheral annular portion is set as an inspection target area so that the colony CL included in the outermost peripheral annular portion is also an inspection target. Then, the image generation unit 42 of the present embodiment includes the image of the sample S shown in FIG. 2 as an image including the inspection target image area KA, that is, the image of the sample S including the side wall portion 30a cut by the outer peripheral contour line of the petri dish 30. To get. The image generation unit 42 detects the outer contour of the petri dish 30 by detecting the density of the image, and acquires an image of the sample S shown in FIG. 2 by cutting out the image inside the detected outer contour. .

  The extraction unit 43 extracts colony candidate regions from the inspection target image region KA. Here, the colony candidate refers to an area portion having a high possibility of colony in the inspection target image area KA. The colony candidate corresponds to a colony CL and a foreign substance N such as a bubble B. Then, the extraction unit 43 detects the density of the colony candidate in the inspection target image area KA, so that the density value (gradation value in gray scale) is higher than the density value of the culture medium M (gradation value). As the lower side), a region (dark region) having an area larger than the set concentration and exceeding the set area is extracted, and the extracted dark region is set as a colony candidate CK (see FIG. 5). .

  As shown in FIG. 4 (a), the outermost peripheral area A2 of the petri dish 30 has the density of the medium M due to the influence of light refracted by the side wall 30a and the relatively thick meniscus portion of the medium M. Since it has changed, it is difficult to accurately extract a colony candidate region whose concentration is higher than that of the medium M and whose density value is less than the set concentration. Further, the side wall 30a extends in an arc shape near the colony CL. Here, the extraction process for extracting the dark and dark area is a process of dividing the area along the boundary (contour) with the culture medium of the area, and the process is strong in the X direction and the Y direction, It is weak to processing in an oblique direction that intersects with the Y direction. The side wall portion 30a of the petri dish 30 and the light and dark circles made of refracted light at the side wall portion 30a and the medium rich region at the meniscus portion extend in an arc shape along the side wall portion 30a, both in the X direction and in the Y direction. Since there are portions extending in the intersecting diagonal direction, processing in the diagonal direction is required when extracting the area of the colony candidate CK while avoiding the side wall 30a and the like.

  Therefore, in the present embodiment, as shown in FIG. 4 (b), the outermost peripheral area A2 is linearly developed along the X direction along with the side wall part 30a, the shaded ring, and the meniscus part by polar coordinate transformation. Convert to BI. Then, enlargement processing for enlarging the belt-like image BI at a predetermined magnification in the Y direction orthogonal to the X direction, which is the extending direction of the side wall portion 30a, creates a belt-like enlarged image LI shown in FIG.

  In performing the extraction process for extracting the colony candidate in the outermost peripheral area A2, the extraction unit 43 performs the above-described polar coordinate conversion process and the enlargement process to create the band-shaped image BI and the band-shaped enlarged image LI. And the extraction part 43 acquires the coordinate of a colony area | region from the strip | belt-shaped expansion image LI, and specifies the area | region of a colony candidate in the original coordinate system based on the acquired coordinate.

  Fig.5 (a)-(i) shows the example of a colony candidate. 5A to 5E are examples in which the colony candidate is a colony CL, FIGS. 5F and 5G are examples in which the colony candidate is a bubble B, and FIGS. 5H and 5I are colonies. The candidate is an example in which the colony CL and the bubble B are connected or overlapped into one. The colony candidate is obtained by extracting an area where the contrast is darker than a threshold value.

  FIG. 5A is an example of a colony CL that is circular and has a dark gray color or black color. FIG.5 (b) is an example of the colony CL which has the shape of an ellipse and a triangle, and has dark gray or black. This kind of circular colony CL is extracted as a colony. FIG. 5C shows an example of a circular colony CL having an outer peripheral region that is dark gray and an inner peripheral region that is black. Since the dark gray outer peripheral region is darker than the culture medium, and the overall gray value including the outer region and the inner region is less than the set value, it is extracted as a colony candidate. FIG. 5D shows an example in which two circular colonies CL having an outer peripheral area dark gray and an inner peripheral area black are connected or overlapped. Since the entire area including the outer area and the inner area is darker than the culture medium, and the entire gray value is less than the set value, the colony candidate is extracted. There is a constriction at the connection point of two colonies CL, and when such a constriction is detected for a colony candidate, and the constriction is detected, the colony candidate is divided into two at the constricted part. CL is counted separately. FIG. 5E shows an example in which a plurality of circular colonies CL having dark gray color or black color are connected or overlapped. A plurality of colonies CL that are connected or overlapped are darker than the culture medium, and the overall gray value is less than the set value. There is a constriction d (see FIG. 6B) at a connection point of a plurality of colonies CL (three in the example in the figure), and such constriction d is detected for the colony candidate, and the constriction d is detected. Then, the colony CL is counted separately by separating the colony candidates into a plurality (three) of the colonies d. Therefore, the colonies CL shown in FIGS. 5A to 5E are detected as colony candidates, and the colonies CL are individually counted.

  Since the bubble B shown in FIG. 5 (f) has a dark gray or black annular shape, the bubble B is determined to be the bubble B by the circular determination for determining whether or not the bubble is circular. However, as shown in FIG. 5 (g), in the case of an annular or semi-annular bubble B that is partially cut, it is not determined as a bubble in the annular determination.

  In addition, as shown in FIG. 5 (h), when the colony CL and the annular bubble B are connected or overlapped, or as shown in FIG. 5 (i), the colony CL and the semicircular bubble B When are connected or overlapped, it is difficult to count colonies CL.

  The foreign substance removal processing unit 44 performs a foreign substance removal process for extracting a colony by performing a foreign substance removal process for removing a foreign substance on a colony candidate. In this example, the foreign matter removal processing unit 44 performs foreign matter removal processing on the colony candidates extracted by the extraction unit 43. Further, in this example, the foreign substance removal processing unit 44 applies to a bubble candidate (an example of a foreign substance candidate) that is determined by the second determination unit 46 to include a bubble B (an example of a foreign substance) among colony candidates. Apply foreign matter removal.

  The first determination unit 45 determines whether or not the colony candidate determined by the second determination unit 46, which will be described later, as possibly containing bubbles is a bubble B as an example of a foreign object. In this determination process, it is determined whether the colony candidate is circular. The determination process performed by the first determination unit 45 corresponds to an example of a first determination step.

  The 2nd determination part 46 determines whether the convexity degree of a colony candidate is below a setting value. The image generation unit 42 performs a connection process in which both ends of the bubble candidate BK determined by the second determination unit 46 to have a convexity of less than or equal to a set value are connected by an auxiliary line. Note that the determination process performed by the second determination unit 46 corresponds to an example of a second determination step, and the process of connecting both ends of the bubble candidates performed by the image generation unit 42 with an auxiliary line is an example of the connection process step. Equivalent to.

  The 3rd determination part 47 determines whether the colony candidate after the foreign material removal process by the foreign material removal process part 44 is a separation object. Here, the separation target refers to a colony candidate including a plurality of colonies. In this example, the area is determined by the area of the colony candidate and the aspect ratio (aspect ratio) indicated by the ratio of the vertical side / horizontal side of the rectangle circumscribing the colony candidate area (the circumscribed rectangle). Those whose ratio exceeds the set value and has a long shape are defined as separation targets. The determination process performed by the third determination unit 47 corresponds to an example of a third determination step.

  A part of the bubble filter function is configured by the first and second determination units 45 and 46, and the colony candidates extracted by the extraction unit 43 are classified as bubble candidates BK that may be bubbles and bubbles that are not possible. Judgment processing is performed in the bubble filter processing for sorting into colony candidates CK.

  The counting unit 48 counts the number of colonies. The counting unit 48 employs a counting method according to the method selected by the method selection information. Specifically, in the case of the first counting method (rotation method), colonies in the inspection target image area KA are counted using a plurality of images having different rotation angles acquired by photographing the sample S a plurality of times at different rotation angles. . Further, in the case of the second counting method (estimation method), the center of the outermost peripheral region A2 and the central region A1 and the outermost peripheral region A2 in which the inspection target image region KA is divided into the inner side and the peripheral side using the image obtained by photographing the sample S. The number of colonies in the area A1 is counted, the number of colonies in the outermost peripheral area A2 is estimated to be a predetermined ratio with respect to the number of colonies in the central area A1, and the number of colonies is obtained by integrating both colonies.

  The control unit 41 displays the colony counting result by the counting unit 48 on the monitor 33. Further, the monitor 33 displays an image of the sample S taken by the camera 16 as shown in FIG. 2, and the image includes a mark surrounding the detected colony CL and a mark surrounding the foreign matter N such as the bubble B. Are superimposed and displayed in different colors. For this reason, the inspector can confirm the inspection result while visually grasping the distribution state of the colonies CL in the culture medium M and the contamination state of the foreign matter N.

  Next, the foreign matter removal process performed by the foreign matter removal processing unit 44 will be described in detail with reference to FIGS. In the present embodiment, shape extraction processing is adopted as foreign matter removal processing. The shape extraction process is a process in which a circle C having a specified diameter (see FIG. 7) is inscribed in the bubble candidate area, and a set area of the inscribed circle C group is extracted. The diameter of the circle C is used as a parameter. In the present embodiment, the diameter is specified as a parameter that is larger than the thickness of the annular portion of the bubble (the maximum thickness that can be assumed) and not more than the diameter of the smallest colony to be detected. For this reason, a region having a shape size in which a circle having a specified diameter can be inscribed remains as a colony region, and a region in which the circle C cannot be inscribed (for example, a bubble region) disappears. For this reason, a curved area (arc-shaped area) having a relatively narrow width, such as an annular or arc-shaped shadow formed on the periphery of the bubble B, is erased because the circle C having a specified diameter cannot be inscribed.

  In the example shown in FIG. 7A, the region CA1 of the colony CL that can be inscribed by the circle C having the specified diameter is extracted as a collection region of the inscribed circle C, and the bubble C that cannot be inscribed by the circle C having the specified diameter. The area B of B is erased. For this reason, the extracted substantially circular colony area | region CA2 shown in FIG.7 (b) remains.

  In addition, as shown in FIG. 7C, when the area of the colony CL is considerably larger than the circle C having the specified diameter, an area where the inscribed circle C does not pass through the center of the shape extraction area SA is formed. As shown in d), the shape extraction area SA extracted as a collection area of the inscribed circle C having a specified diameter becomes a ring shape having a hole H at the center. In this case, since this ring shape is regarded as a bubble and is not determined as a colony, the shape extraction processing is performed while increasing the specified diameter stepwise until the hole H cannot be formed. Is performed a plurality of times so that the non-circular colony region CA2 shown in FIG. 7E is extracted.

  For this reason, the annular bubble B shown in FIG. 8A is erased by the shape extraction process (foreign matter removal process) because the circle C having the specified diameter cannot be inscribed. Further, the arc-shaped bubble B shown in FIG. 8B is also erased because the circle C having the specified diameter cannot be inscribed. Further, the foreign matter N such as fibrous dust shown in FIG. 8C is also erased because the circle C having the specified diameter cannot be inscribed.

  In addition, as shown in FIGS. 8D and 8E, when the bubble B and the colony CL are connected or overlapped, the bubble B that cannot be inscribed by the circle C having the specified diameter is erased, and the circle C is inside. The shape of the colony CL that can be contacted is extracted and remains as the extracted colony region CA2. At this time, as shown in FIG. 8E, when the colony CL is an ellipse (a shape other than a circle) and the maximum curvature of the ellipse is larger than the curvature of the designated circle C, a circle inscribed in the ellipse The shape extracted as the aggregate region is extracted as an elliptical colony region CA2 having a shorter diameter than the original ellipse or a circular colony region CA2 having a shorter diameter than the original ellipse. For example, if the colony CL has a triangular shape, the bubble B is erased, and the corner of the triangle that can be inscribed by the designated circle C is extracted as a shape rounded by an arc having a designated diameter.

  Next, the operation of the inspection system 11 will be described. Hereinafter, the microorganism detection process of the computer 38 will be described with reference to the flowcharts shown in FIGS. The microorganism detection process is performed by the detection processing device 40 shown in FIG.

  The inspector sets the sample S on the stage 22 of the examination room 12a. This is the result of the inspector operating the input device 32 before starting the test, and selecting the desired one of the test target information including the microorganism species to be tested and a plurality of detection methods prepared in advance. Setting information including method selection information and the like is input to the personal computer 13. The various setting information that has been input is stored in the memory 36. When the inspector performs an inspection start operation using the input device 32, the microorganism detection processing is started by the computer 38 (detection processing device 40). In the microorganism detection process of the present embodiment, a detection process for detecting a colony of a specific fungus as an example of a microorganism present in the image area to be inspected based on image data obtained by photographing the sample S by the camera 16; And a counting process for counting the number of detected colonies.

  First, in step S <b> 11 in FIG. 9, the computer 38 acquires method selection information from the memory 36. In this example, since the first counting method (rotation method) and the second counting method (estimation method) are prepared as detection methods, the detection method is selected by the inspector based on the method selection information. Grasp one.

  In step S12, the inspection object is imaged with a camera to obtain image data. Here, the method for obtaining an image by photographing with a camera differs depending on the method selected by the inspector. That is, in the case of the first counting method, first, imaging is performed at the set position, and then the motor 26 is driven to rotate the stage 22 to rotate the stage 22 so that the sample S (that is, the petri dish 30) is set at a set angle (360 degrees / N (where N Is a natural number greater than 2)) and rotates the next shot. In this way, N types of image data are acquired while rotating the sample S by a set angle. Here, N is preferably a predetermined value in the range of 3-20. On the other hand, when the second counting method is selected, the camera 16 captures the sample S at the set position at that time and acquires image data. Note that a plurality of images may be captured under the same position condition of the sample S, and a process of averaging the captured images may be performed to acquire one image data.

  In step S13, an inspection target image area is extracted based on the image data. As the inspection target image area KA, the outer periphery of the petri dish 30 is detected from light and shade, and the image area inside the outer periphery is extracted. At this time, the reason why the image region inside the outer periphery of the petri dish 30 is extracted in this way is that the colony CL that appears through the tapered side wall portion 30a also exists and includes the side wall portion 30a that overlaps the culture medium M. Is extracted as the inspection target image area KA. In this way, it is possible to detect the colony CL in contact with the side wall 30a and the colony CL generated in the vicinity of the side wall 30a.

  In step S14, the inspection target image area is divided into a central area and an outermost peripheral area. That is, as shown in FIG. 2, the inspection target image area KA is divided into a central area A1 and an outermost peripheral area A2. The outermost peripheral area A2 has a predetermined width (as an example, 0.1D) within a range of 1/5 to 1/20 with respect to the diameter D of the circular inspection target image area KA, and is circular along the side wall 30a. It extends in a ring shape.

  In step S15, colony candidates are extracted. Here, the extraction destination area from which the colony candidate is extracted differs according to the method selected by the inspector. That is, in the case of the first counting method (rotation method), colony candidate extraction processing is performed in both the central region A1 and the outermost peripheral region A2. On the other hand, in the case of the second counting method (estimation method), colony candidate extraction processing is performed for the central region A1, but colony candidate extraction processing is not performed for the outermost peripheral region.

  In this colony candidate extraction process, a region having a gray value (grayscale tone value (pixel value)) higher than a set value in the extraction target region corresponding to the method in the inspection target image region is extracted as a colony candidate. That is, if the pixel value is 256 gradations, a region (dark region) where the pixel value is a value equal to or less than the set value 100 is extracted as a colony candidate. The reason why the colony candidates are extracted based on the gray value and the set value is that the colony CL appears darker than the medium M in the image taken by the camera 16.

  Here, when a dark area is extracted from the image, the closed area is extracted as a colony candidate by obtaining a light / dark boundary line and making one round of the closed area. In the case of the first counting method, in addition to the central region A1, the outermost peripheral region A2 is also a colony candidate extraction target, but in the outermost peripheral region A2, the side wall 30a extends in a circular shape on the outer peripheral side, The light is bent at the side wall 30a, and a light and shade ring is formed on the medium M. It is relatively difficult to divide the colony region by distinguishing this kind of optical density circle from the colony candidate boundary line.

  Therefore, in this embodiment, when extracting colony candidates CK in the outermost peripheral area A2, first, polar coordinate conversion is performed on the outermost peripheral area A2, and the strip-shaped image BI (FIG. The density of the colony candidate (in this case, polar coordinates) is acquired by performing density determination on the band-like enlarged image LI obtained by enlarging b)) in the Y direction. And the colony candidate in outermost periphery area | region A2 is extracted by acquiring XY coordinate from the polar coordinate of the acquired colony candidate.

  Here, the colony candidate CK includes only one colony CL (FIGS. 5A to 5D), a plurality of colonies CL connected or overlapped (FIG. 5E), bubble B 5 (FIGS. 5 (f) and 5 (g)) and those in which a colony CL and a foreign substance N such as a bubble B are connected or overlapped (FIGS. 5 (h) and (i)). The bubble B has an annular shape in which a hole (for example, a white hole) in a light region is inside a dark region extending in an annular shape along the outer periphery thereof.

  In step S16, bubble filter processing is performed. In this bubble filtering process, the colony candidate CK extracted in step S15 is classified into a bubble candidate BK (an example of a foreign substance candidate) that is likely to include the bubble B and a colony candidate that is unlikely to include the bubble B. It is. This bubble filter processing is performed by the computer 38 executing a bubble filter processing routine shown in FIG. If it determines with colony candidate CK being a bubble candidate, it will progress to step S17, and if it determines with not a bubble candidate but a colony candidate, it will progress to step S18.

  Here, the details of the bubble filter processing will be described according to the flowchart of the bubble filter processing routine shown in FIG. This bubble filter process is sequentially performed for each colony candidate CK.

  In step S31, it is determined whether or not the convexity is equal to or less than a set value. Here, the colony candidate CK may contain foreign substances such as bubbles. As described above, the bubbles include a deep annular shape and a deep arc shape. Since a dark circular object has a hole (for example, a white hole) in a light region on the inner side, it can be understood that it is a bubble B if an annular determination is made to determine whether or not the hole has a hole. However, since the bubbles B appearing in a dark arc shape are not circular, it is difficult to distinguish them from colonies even by circular determination. Therefore, the colony candidate CK is pre-processed so that the arc-shaped bubble B can be determined as a bubble by circular determination. Each processing of step S31 and the next step S32 corresponds to this preprocessing.

  Here, the convexity (convexity) is a value indicating the degree to which the region is convex, and in this example, is given as a shape factor for the convexity of the region. If the area of the convex hull is Fc and the area of the region is Fo, the shape factor K is expressed by K = Fo / Fc. The convex hull is a minimum convex set (convex region) including a given set (region). For example, the convex hull is a figure created by the rubber film when the region is wrapped with the rubber film. When the region is a convex region such as a circle, the shape factor K is 1, and when there is a dent or hole in the region, the shape factor K is less than 1. In this example, both the annular and arc-shaped bubbles B have the convexity below the set value, and the set value is set such that the convexity of the colony CL such as a circle, an ellipse, or a triangle exceeds the set value. Yes. The convexity is not limited to the one defined by the shape factor K, and may be a convexity defined by another method capable of measuring the degree of convexity of the region.

  And if it is the bubble B, since there is a hole or a dent in either an annular shape or an arc shape, the degree of convexity becomes a set value or less. Further, since the colony CL is a convex shape such as a circle, an ellipse, or a triangle, the degree of convexity is larger than the set value. For this reason, in this step S31, by performing convexity determination for determining whether or not the convexity of the colony candidate CK is equal to or less than the set value, the colony candidate CK is considered to be a colony candidate having a high possibility of containing the bubble B ( A bubble candidate) and a colony candidate that is highly likely not to contain a bubble are separated. In this convexity determination, if the convexity is equal to or less than the set value, the process proceeds to step S32. On the other hand, if the convexity is larger than the set value, it is determined as a colony candidate, and the process proceeds to step S18. For example, in the case of a colony candidate CK in which a plurality of colonies CL shown in the right diagram of FIG. 6B are connected or overlapped to form an arcuate region, the degree of convexity is equal to or less than the set value, and the process proceeds to step S32. Moreover, as shown in FIG.5 (e), in the case of the colony candidate CK which forms the linear form although the several colony CL is connected or overlapped, since convexity degree exceeds a preset value, it progresses to step S18. In the present embodiment, the process of step S31 in which the second determination unit 46 determines whether the convexity of the colony candidate CK is equal to or less than the set value corresponds to an example of a second determination step.

  In step S32, both ends of the colony candidate are connected by an auxiliary line. In the case of an arc-shaped bubble B as shown in FIG. 6A, when both ends of the colony candidate CK are connected by an auxiliary line AL having a predetermined thickness, a semicircular ring is formed. In addition, as shown in FIG. 6B, in the case of a colony candidate CK extracted as one region even though a part of a plurality of colonies CL connected or overlapped is slightly cut, both end portions of the colony candidate CK Are connected by the auxiliary line AL, it is not a completely closed ring, but a part of the ring is cut off. In the present embodiment, the process of step S32 in which the image generation unit 42 connects both ends of the colony candidate CK with the auxiliary line AL corresponds to an example of a connection processing step.

  In the next step S33, an annular determination (bubble determination) is performed. That is, it is determined whether or not the colony candidate CK has an annular shape with a white hole whose density is lighter than the threshold. If the colony candidate CK is determined to be circular, it is determined as a bubble candidate BK, and the process proceeds to step S17. For example, in the case of the colony candidate CK shown in FIG. 5 (f), the right view of FIG. 6 (a), and the colony candidate CK shown in FIG. On the other hand, if it determines with the colony candidate CK not being cyclic | annular, it will progress to step S18. For example, as shown in the right figure of FIG. 6 (b), when a plurality of colonies CL are connected at a plurality of places and there is a slight gap that is not connected at least at one place, a part of the ring is cut off. Therefore, it is determined that it is not annular, and the process proceeds to step S18. Thus, the colony candidate CK in which a part of the ring is cut is regarded as a plurality of colonies CL connected or overlapped and becomes a separation target in later processing. Note that the auxiliary line AL added to connect both ends of the colony candidate CK after the circular determination is deleted. Moreover, in this embodiment, the 1st determination part 45 corresponds to an example of the 1st determination step in the cyclic | annular determination process of step S33 which determines whether the colony candidate CK is cyclic | annular.

  Returning to FIG. 9, in step S17, bubble removal processing is performed. A bubble removal process is performed on the bubble candidate BK (also a broad colony candidate CK) determined to be annular. In this example, as the bubble removal process, a shape extraction process is performed to extract the shape of the area portion having a size exceeding the threshold from the area of the colony candidate CK. More specifically, the shape extraction process of this example is a process of extracting a collection region of circles C in which the diameter of the circle C is designated as a threshold and the circle C having the designated diameter can be inscribed in the region of the bubble candidate BK. . Hereinafter, this shape extraction process will be described by taking, as an example, a bubble candidate BK in which the colony CL and the bubble B are connected or overlapped as shown in FIGS.

  As shown in FIGS. 7A and 7C, a process of extracting a set region of circles C having a specified diameter that can be inscribed in the region of the bubble candidate BK is performed. In the example of FIG. 7, a plurality of circles C having a specified diameter inscribed in the region of the bubble candidate BK are drawn (four in the example of FIG. 7A and six in the example of FIG. 7B). Is a collection region of an infinite number of circles C that are inscribed at different positions in the region of the bubble candidate BK. In other words, it becomes the region of the locus of the circle C when the circle C having a specified diameter that is inscribed in the region of the bubble candidate BK is maintained in a state in which the circle C is moved around the region. Further, since the width of the arc-shaped bubble area BA forming the bubble B is smaller than the specified diameter, a circle C (a broken line in FIGS. 7A and 7C) having a specified diameter is included in the bubble area BA. I can't touch. Therefore, the region in which the circle C having the specified diameter cannot be inscribed is deleted because its shape is not extracted. As a result, in the example of FIG. 7A, the arc-shaped bubble area BA is deleted, and for example, a circular colony area CA1 having a size in which the circle C having a specified diameter can be inscribed remains, and FIG. As shown, the circular colony area CA2 is extracted. That is, by the shape extraction process, the bubble area BA that is the portion of the bubble B shown in FIG. 7A is erased, and the circular colony CL shown in FIG. 7B remains.

  Further, as shown in FIG. 7C, when the colony area CA1 forming the colony CL in the bubble candidate BK has a diameter (short diameter) that is considerably larger than the specified diameter, the specified diameter inscribed in the colony area CA1 The shape extraction area SA indicated by the gathering area of the circle C becomes an annular shape having a hole H at the center as shown in FIG. In this case, if an annular determination is made after the shape extraction process, it will be determined as a bubble B. Therefore, a process for deeply filling the hole H is performed after the shape extraction process, and the hole H is formed as shown in FIG. Let it be a colony area CA2 that does not have. If it is clear from the ratio between the specified diameter and the assumed maximum colony diameter that the shape extracted after the shape extraction processing is not circular, the above-described processing for deeply filling the hole can be omitted and is not essential.

  By this shape extraction process, both the annular bubble B shown in FIG. 8A and the arc-shaped bubble B shown in FIG. 8B, which are bubble candidates BK, are erased. Further, the linear foreign matter N shown in FIG. 8C which is the bubble candidate BK is similarly erased by the shape extraction process. Further, in the case of the bubble candidate BK in which the annular bubble B and the colony CL shown in FIG. 8D are connected or overlapped, and the arc-shaped bubble B and the colony CL shown in FIG. In the case of overlapping bubble candidates BK, as shown in the lower diagrams of FIG. 8D and FIG. 8E, the bubbles B are erased and the colony CL whose shape has been extracted remains. In this case, in the example of FIG. 8E, the elliptical colony CL is extracted as a circular colony region CA2 by the shape extraction process.

  On the other hand, in step S18 in FIG. 9, colonies are counted. That is, a counting process for detecting (extracting) colonies and counting a colony candidate CK that is unlikely to contain bubbles in the bubble filtering process is performed. In this counting process, colonies are separately counted in the central area A1 and the outermost peripheral area A2 using a counting method according to the counting method selected at that time.

  First, the colony counting process in the central area A1 is performed. Colonies are extracted from the roundness and area of colony candidates. If the circularity V of the colony candidate CK exceeds the threshold and the area satisfies the area condition (threshold condition), it is determined as a colony. Here, the circularity V in this example is expressed by V = 4πS1 / (L1 ^ 2) where S1 is the area of the region and L1 is the peripheral length of the region. Here, the symbol “^” represents a power. When the shape of the region is a perfect circle, the circularity V takes a maximum value and V = 1. The circularity V takes a value of less than 1 when the region has a shape other than a perfect circle, and takes a value closer to 1 as the shape is closer to a circle, and a value closer to 0 (zero) as the shape is farther from the circle. Further, as the area condition (threshold condition), the area Sc of the colony candidate CK region is set to satisfy an area condition Slower ≦ Sc ≦ Superper that is not less than the lower limit area Slower and not more than the upper limit area Superper. In addition, as long as the circularity is defined by a calculation formula in which the value increases uniformly as the shape of the region is closer to a circle, a value defined by another calculation formula may be used.

  When the circularity V and the area satisfy the respective threshold conditions and are determined to be colonies, the determined colonies are marked, and coordinates and information indicating that the colonies are stored in a predetermined storage area of the memory 36 Is remembered. And the count process which counts the number of the colonies which have the coordinate which belongs to center area | region A1 among the marked colonies is performed, and the colony number Cc in center area | region A1 is acquired. The counting process in the central area A1 is common to each counting method.

  Next, the colony counting process in the outermost peripheral region is performed. The number of colonies in the outermost peripheral area A2 is counted by a method according to the counting method. In the case of the first counting method (rotation method), for the colony candidates in the outermost peripheral region A2 in the plurality of inspection target image regions KA having different rotation angles, the circularity and area are the same as in the central region A1. Extract colonies from Then, the corresponding coordinates between the outermost peripheral areas A2 with different rotation angles are compared, and if there are a plurality of colonies that were one in the outermost peripheral area A2 in the corresponding coordinates of the other outermost peripheral area A2, Use the larger number. Colony counting is performed by this method to obtain the number of colonies Co in the outermost peripheral area A2. In the case of the second counting method (estimation method), the number of colonies Co in the outermost peripheral region A2 is acquired by multiplying the number of colonies Cc in the central region A1 by a predetermined ratio.

  In step S19, the count results of the central area and the outermost peripheral area are integrated. That is, the number of colonies Cc in the central area A1 and the number of colonies Co in the outermost peripheral area A2 are added to obtain an integrated colony number Ca (Ca = Cc + Co).

  In step S20, it is determined whether or not it is a separation target. In this example, the colonies targeted for counting in step S18 and the colonies extracted by the bubble removal process are targeted for determination. In this example, whether or not it is a separation target is determined by the area of the colony candidate CK and the aspect ratio (aspect ratio) of the circumscribed rectangle of the colony candidate CK. That is, when the area of the colony candidate CK exceeds the threshold and the aspect ratio exceeds a set value greater than “1”, it is determined as a separation target. Here, for example, the set value is set to a value smaller than the aspect ratio of the circumscribed rectangle when two colonies having the same diameter are connected or overlapped with the maximum allowable overlap amount. For example, the colony candidate CK shown in FIGS. 5D, 5E, and 6B is the separation target. If the colony candidate is a separation target, the process proceeds to step S21, and if not, the process proceeds to step S22. The process of step S20 corresponds to an example of a third determination step.

  In step S21, colonies are separated. That is, the separation process for separating the colony candidates CK to be separated into a plurality of colonies CL is performed. In this example, a constricted portion is detected from the density of the colony candidate CK, and the region of the colony candidate CK is separated into a plurality of regions at the constricted portion, so that the colony CL is separated into a plurality of colonies CL. For example, in the left diagram of FIG. 6B, a portion of a constriction d (concave portion) of a plurality of colonies CL is detected, a region of colony candidate CK is separated into a plurality of regions by the detected constriction d, and each of the separated regions is detected. Is newly set as a colony candidate CK. Then, the number of new colonies separated is counted.

  In step S22, the counting results are integrated. That is, the number of colonies corresponding to the sum of the number of colonies Ca integrated in step S19, the number of colonies Cs extracted by the bubble removal process, and the colony increment number ΔC increased by the separation process (S21) is calculated. The total number of colonies Ct in S is obtained (Ct = Ca + Cs + ΔC). Note that the processing in step S22 corresponds to an example of a counting step.

  In the next step S23, the count result is displayed on the monitor 33. In the image of the sample S displayed on the monitor 33, the mark surrounding the colony CL and the mark surrounding the foreign object N are superimposed and displayed in different colors. Furthermore, the number of colonies present in the colony region to which one mark is attached is superimposed and displayed as a number. Therefore, the distribution status of the detected colonies CL can be visually grasped, the number of colonies existing in one continuous area can be grasped, and the distribution status of the foreign matter N can also be grasped separately from the colonies CL. .

As described above in detail, according to the first embodiment, the following effects can be obtained.
(1) The shape extraction process is performed on the bubble candidate BK. Therefore, even if the bubble B and the colony CL are connected or overlapped in the image, the bubble B is removed to detect the colony CL, and the detected colony CL can be counted. Therefore, the colony detection accuracy and colony counting accuracy of the inspection system 11 and the detection processing device 40 can be increased.

  (2) Since the shape extraction process performed as an example of the foreign substance removal process has a predetermined size (designated diameter) inscribed in the region when extracting the shape, the shape extraction process is relatively simple. . Further, since the region where the circle C cannot be inscribed can be erased by the shape extraction process, the colony region CA2 obtained by extracting the shape of the colony region CA1 where the circle C can be inscribed while removing the annular or arc-shaped bubbles B is obtained. Can leave. Therefore, even if the colony CL and the bubble B are connected or overlapped, the bubble B can be appropriately removed.

  (3) As an example of the second determination step, the second determination unit 46 determines whether or not the convexity of the colony candidate CK is equal to or less than a set value. The colony candidate CK having a high possibility of containing the bubbles and the colony candidate having a low possibility of containing the bubbles B can be distinguished. Then, the image generation unit 42 performs a connection processing step (S33) in which both end portions of the colony candidate CK having a convexity degree equal to or less than the set value and highly likely to include the bubbles B are connected by the auxiliary line AL. Furthermore, the 1st determination part 45 performs cyclic | annular determination (S34) as an example of a 1st determination step. As a result, it is possible to extract the bubble candidate BK that requires the foreign substance removal process (shape extraction process) from the colony candidate CK. Therefore, it is possible to reduce the number of bubble candidates BK (broadly defined colony candidates CK) to be subjected to the foreign substance removal processing. As a result, the colony counting processing speed by the inspection system 11 and the detection processing device 40 can be increased.

  (4) Since the separation target among the colony candidates after the foreign substance removal processing is separated into a plurality of colonies, the colony counting accuracy by the inspection system 11 and the detection processing device 40 can be further improved.

(5) By implementing one of the first counting method and the second counting method, the colony counting accuracy of the outermost peripheral area A2 is increased, and as a result, the colony counting accuracy of the detection processing device 40 is increased.
(6) Since colony candidates are extracted (acquisition of coordinates in this example) using the band-shaped image BI obtained by polar-coordinate conversion of the outermost peripheral area A2, the colony candidates CK can be extracted relatively accurately. For example, when the polar coordinate conversion is not performed, the processing performed in the X direction and the Y direction when extracting the colony region is obstructed by the arc-shaped side wall portion 30a of the petri dish 30 and the light and shade ring formed by the refraction of light at the side wall portion 30a. It becomes difficult to specify the colony region. However, in the present embodiment, the side wall 30a of the petri dish 30 and the light and dark circles are each converted into a straight line parallel to the X direction by polar coordinate conversion, so that it is difficult to disturb the processing in the X direction and the Y direction. It becomes easy to acquire the coordinates of the area. For this reason, the shape of the region can be extracted relatively accurately without leaking colony candidates.

  (7) In addition to the bubbles B, the fibrous or linear foreign matter N can also be removed by the shape extraction process which is an example of the foreign matter removal process. Therefore, also from this point, the colony counting accuracy can be improved.

The embodiment is not limited to the above, and may be modified as follows.
In the extraction process, the extraction unit 43 acquires the polar coordinates of the colony candidate in the strip-shaped image BI after the polar coordinate conversion of the outermost peripheral area A2, acquires the coordinates of the original coordinate system from the polar coordinates, and extracts the area from the original However, it may be performed up to extraction of a colony candidate region in the band-like image BI. Further, extraction processing for extracting colony candidates from the band-shaped enlarged image LI may be performed. In addition, in the band-shaped image BI or the band-shaped enlarged image LI, the convexity degree determination of the colony candidate (second determination step), the connection processing step of connecting both ends of the colony candidate with an auxiliary line, and the colony candidate is a foreign object (bubble). An annular determination (an example of a first determination step) may be performed to determine whether or not. Further, the colony counting process may be performed on the band-shaped image BI or the band-shaped enlarged image LI. According to this method, colony candidates in the outermost peripheral area A2 can be easily extracted, and various processes including removal of foreign matters can be performed without taking correspondence from the polar coordinates to the original coordinates.

The colony candidate extraction process based on the density or color difference performed by the extraction unit 43 may include an edge detection process.
-You may perform a foreign material removal process to all the colony candidates extracted at the extraction step. Although the processing time required for the foreign substance removal processing becomes longer, the detection accuracy and counting accuracy of microorganisms are improved.

  -You may make it perform a connection process step and circular determination (an example of a 1st determination step) to all the colony candidates which the extraction part 43 extracted. According to this method, a colony can be detected by removing foreign matters although the number of objects of the connection process and the circular determination process is increased.

  -You may abbreviate | omit a connection process step (S32). Even in this method, colonies can be detected by removing the annular bubbles. Furthermore, the annular determination (S33) may be abolished. According to this method, a colony can be detected by removing circular and arc-shaped bubbles by applying a foreign substance removal process (for example, a shape extraction process) to bubble candidates having a convexity of not more than a set value.

  -The counting step and counting unit may be eliminated. That is, the present invention may be applied to a microorganism detecting apparatus that does not count colonies but performs colony detection as in the microorganism counting apparatus. According to this microorganism detection apparatus, colonies connected to or overlapping with bubbles can also be detected.

  In the shape extraction process, the shape inscribed in the area of the colony candidate is a circle, but other predetermined shapes such as an ellipse, a polygon such as a triangle, a quadrangle, a pentagon, a hexagon, a trapezoid, and a rhombus may be used. Alternatively, the shape extraction may be performed by extracting a region that becomes a locus when the predetermined shape is rolled in a state inscribed in the colony candidate region.

-You may detect a colony by the method which does not divide a test object image area | region into a center area | region and an outermost periphery area | region. Further, the colony may be inspected by excluding the outermost peripheral region from the inspection target.
・ The shooting time and counting time may be shifted. Images obtained by photographing a plurality of samples S at the photographing time are sequentially stored in the memory 36, and thereafter, for example, the images are read from the memory 36 at a necessary time one hour to several days later, and a plurality of colony counting processes for the images are collected. You may go. In this case, when the inspector performs a colony counting instruction operation using the input device 32 of the inspection system 11, the computer 38 that has received this instruction executes the program PR, and performs an extraction step, a foreign matter removal step, and a counting step.

  -You may extract a colony candidate using a color image using a color camera. In this case, colony candidates may be extracted from the difference in color between the culture medium and the colony based on the gradation value of the color (for example, RGB) instead of the gray value. Further, an auxiliary line of a predetermined color (for example, bubble color) may be added in the circular determination, and the circular determination may be performed by color determination. When a color camera is used, some of the plurality of processes including extraction processing, convexity determination, ring determination, and the like may be performed by color determination, and some other processing may be performed by shading determination. .

・ Polar coordinate conversion is not necessary. Extraction of colony candidates, extraction (detection) of colonies, and colony counting may be performed with the circular peripheral region without performing polar coordinate conversion.
-Microorganisms to be detected (counted) are bacteria that are generally involved in food contamination, including aerobic bacteria, Escherichia coli, intestinal bacteria, yeast, gonorrhea, mold, Staphylococcus aureus, Listeria, Campylobacter, etc. Or that colony may be sufficient.

  -It is good also as a method which abolishes a 1st count system and does not rotate the sample S. FIG. In addition, the second counting method is abolished, and the number of colonies in the outermost peripheral area A2 (an example of the peripheral area) is not estimated as a predetermined ratio with respect to the number of colonies in the central area. And may be counted. In these cases, it is possible to appropriately select whether or not to perform polar coordinate conversion in the process of extracting colony candidates in the outermost peripheral area A2 (an example of the peripheral area).

  DESCRIPTION OF SYMBOLS 11 ... Microorganism test | inspection system, 12 ... Test | inspection part, 13 ... Personal computer, 16 ... Camera, 23 ... Light source, 31 ... Main body, 32 ... Input device, 33 ... Monitor, 36 ... Memory, 38 ... Computer, 40 ... Microorganism detection apparatus Detection processing apparatus as an example, 41... Control unit, 42... Image generation unit, 43... Extraction unit, 44 .. foreign matter removal processing unit, 45 .. first determination unit, 46. 48, a counting unit, PR, a program, S, a sample that is an example of an inspection object, M, a culture medium, KA, an image region to be inspected, A1, a central region, A2, an outermost peripheral region as an example of a peripheral region, CL: Colony, B: Bubble as an example of foreign matter, N: Foreign matter, CK ... Colony candidate, BK ... Bubble candidate, AL ... Auxiliary line.

Claims (8)

A microorganism detection method for detecting microorganisms cultured in a medium,
An extraction step for extracting, as a colony candidate, a region in which a colony of microorganisms may exist based on a difference in color or color from a culture medium in an inspection target image region in an image obtained by photographing a test target including a culture medium; ,
Determining whether the colony candidate is circular, and determining whether the colony candidate is a foreign substance or a colony candidate in which a plurality of colonies are linked, and a circular determination step;
Microorganism detection method characterized by comprising a foreign substance removal step by applying a foreign substance removal process that removes the colony candidates it is determined that the foreign matter in the annular determining step for extracting the colonies.   The microorganism detection method according to claim 1, further comprising a counting step of counting the number of colonies including the number of colonies extracted by the foreign substance removal process. Prior to the annular determination step ,
A convexity determination step for determining whether or not the convexity of the colony candidate is equal to or less than a set value;
Microorganism detection method according to claim 1 or 2, further comprising wherein the kite and a connecting process step of connecting both ends of the convex surface of a set value or less colony candidates auxiliary line. Separation determination step for determining whether or not the candidate for colony after the foreign substance removal processing in the foreign substance removal step is a separation target that may include a plurality of colonies;
The microorganism detection method according to any one of claims 1 to 3 , further comprising a separation step of performing a separation process on the colony candidate determined as the separation target. The foreign matter removing process includes a shape extracting process of extracting a shape of a region having a size exceeding a threshold value in a colony candidate and removing at least a part of a region occupied by a foreign matter other than the colony with respect to the colony candidate. The microorganism detection method according to any one of claims 1 to 4 . Dividing the image area to be inspected into a central area and a peripheral area;
In the extraction step, further comprising a polar coordinate conversion step of polar coordinate converting the peripheral area, any one of claims 1 to 5, characterized in that extracting the colony candidates in the peripheral region in the image of the peripheral region after polar coordinate conversion The method for detecting a microorganism according to one item. A microorganism detection apparatus for detecting microorganisms cultured in a medium,
An extraction unit for extracting a region where a colony of microorganisms may exist as a colony candidate based on a difference in color or color from a culture medium in an inspection target image region in an image obtained by photographing a test target including a culture medium; ,
It is determined whether the colony candidate is circular, and the circular determination unit that determines whether the colony candidate is a foreign substance or a colony candidate in which a plurality of colonies are connected, and
Microorganism detection apparatus characterized by comprising a foreign substance removal processing unit which extracts the colonies subjected to foreign matter removing process of removing foreign matter other than colony to the colony candidates. A program for causing a computer to execute a microorganism detection process for detecting microorganisms cultured in a medium,
On the computer,
An extraction step for extracting, as a colony candidate, a region in which a colony of microorganisms may exist based on a difference in color or color from a culture medium in an inspection target image region in an image obtained by photographing a test target including a culture medium; ,
Determining whether the colony candidate is circular, and determining whether the colony candidate is a foreign substance or a colony candidate in which a plurality of colonies are linked, and a circular determination step;
Program for executing a foreign substance removal step by applying a foreign substance removal process that removes the colony candidates it is determined that the foreign matter in the annular determining step for extracting the colonies.